Elucidating multi-input processing 3-node gene regulatory network topologies capable of generating striped gene expression patterns.

A central problem in developmental and synthetic biology is understanding the mechanisms by which cells in a tissue or a Petri dish process external cues and transform such information into a coherent response, e.g., a terminal differentiation state.

MicroRNA-mRNA Co-sequencing Identifies Transcriptional and Post-transcriptional Regulatory Networks Underlying Muscle Wasting in Cancer Cachexia.

Cancer cachexia is a metabolic syndrome with alterations in gene regulatory networks that consequently lead to skeletal muscle wasting. Integrating microRNAs-mRNAs omics profiles offers an opportunity to understand transcriptional and post-transcriptional regulatory networks underlying muscle wasting. Here, we used RNA sequencing to simultaneously integrate and explore microRNAs and mRNAs expression profiles in the tibialis anterior (TA) muscles of the Lewis Lung Carcinoma (LLC) model of cancer cachexia.

Modeling the evolution of molecular systems from a mechanistic perspective.

Systems biology-inspired genotype-phenotype mapping models are increasingly being used to study the evolutionary properties of molecular biological systems, in particular the general emergent properties of evolving systems, such as modularity, robustness, and evolvability. However, the level of abstraction at which many of these models operate might not be sufficient to capture all relevant intricacies of biological evolution in sufficient detail. Here, we argue that in particular gene and genome duplications, both evolutionary mechanisms of potentially major importance for the evolution of molecular systems and of special relevance to plant evolution, are not adequately accounted for in most GPM modeling frameworks, and that more fine-grained mechanistic models may significantly advance understanding of how gen(om)e duplication impacts molecular systems evolution.

Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space.

Background: Signal transduction networks represent the information processing systems that dictate which dynamical regimes of biochemical activity can be accessible to a cell under certain circumstances. One of the major concerns in molecular systems biology is centered on the elucidation of the robustness properties and information processing capabilities of signal transduction networks. Achieving this goal requires the establishment of causal relations between the design principle of biochemical reaction systems and their emergent dynamical behaviors.

A developmental systems perspective on epistasis: computational exploration of mutational interactions in model developmental regulatory networks.

The way in which the information contained in genotypes is translated into complex phenotypic traits (i.e. embryonic expression patterns) depends on its decoding by a multilayered hierarchy of biomolecular systems (regulatory networks).